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Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data
Emily Breza1, Arun G Chandrasekhar2, Tyler H McCormick3
1Department of Economics, Harvard University.
Abstract:
Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.
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